• Journal of the Korean Institute of Gas
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• v.15 no.1
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• pp.60-67
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• 2011

The interest about new and renewable energy is increasing to reduce the burden of problems by depletion of fossil fuels and air pollutions. For example, LNG/CNG and LPG are expected to be replaced, especially in transportation use, by HCNG mixture and DME-LPG mixture, respectively. Because these new energies are still flammable gases, it is not inherently safe from the explosion. In this research, the quantitative risk analysis for using alternative mixtures in existing recharging facilities has been studied by using three types of explosion models (TNT equivalency model, PHAST and CFD-based FLACS) to manage the risk effectively. The differences of results by models were compared against, and the practical ways of when and how to use these models were suggested. It was also predicted that conventional gas filling stations would be converted as new energy stations without additional explosion risk.

• Journal of the Society of Naval Architects of Korea
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• v.55 no.3
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• pp.215-221
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• 2018

The structural design of offshore installations against explosions has been required to protect vital areas (e.g. control room, worker's area etc.) and minimize the damage from explosion accidents. Because the explosion accident will not only result in significant casualties and economic losses, but also cause serious pollution and damage to surrounding environment and coastal marine ecosystems. Over the past two decades, an incredible efforts was made to develop reliable methods to reduce and manage the explosion risk. Among the methods Quantitative Risk Assessment and Management (QRA&M) is the one of cutting-edge technologies. The explosion risk can be quantitatively assessed by the product of explosion frequency based on probability calculation and consequence analyzed using computer simulations, namely Computational Fluid Dynamics (CFD) and Finite Element Analysis (FEA). However to obtain reliable consequence analysis results by CFD and FEA, uncertainties associate with modeling and simulation are needed to be identified and validated by comparison with experimental data. Therefore, large-scaled explosion test procedure is developed in this study. And developed test procedure can be helpful to obtain precious test data for the validation of consequence analysis using computer simulations, and subsequently allow better assessment and management of explosion risks.

• Journal of Environmental Impact Assessment
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• v.4 no.3
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• pp.1-8
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• 1995

In generally speaking, the purpose of Environmental Impact Assessment(EIA) is to give the environment its due place in the decision-making process by clearly ealuating the environmental consequence of a proposed activity before action is taken. The introduction of conventional EIA is to be seen as an end product of a very long evolutionary process, starting with rudimentary but evolving pollution control measures for air, water, noise, land and chemicals, each governed by separate, and separately administered pieces of legislation. In EIA process, the measures of status, scoping, proposed mitigation and communication have not been very quantitative in their significancy. Of course, the determinations have uncertainity in the implications for significant impacts. To improve the determination of significant impacts, some more comprehensive methodologies of EIA has been proposed with the concepts of risk analysis in the proposed projects. The concepts of risk analysis has been introduced to the expression of human health impairment due to environmental pollutants since the early 1980's. The risk analysis being meant by the statistical significance of impact has a process quantitatively considering uncertainities and importances of ecological systems and human health as well. The process of risk analysis shows assessment, doseresponse in toxicity, exposure assessment and risk characterization. With the risk assessment, it could be suggested for the proper measurements against their anticipated risk in the EIA. This paper deals the priciples developing process and application of the risk-based analysis in EIA.

• Geomechanics and Engineering
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• v.24 no.3
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• pp.281-293
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• 2021

Uncertainties in geomechanical input parameters which mainly related to inappropriate data acquisition and estimation due to lack of sufficient calibration information, have led wellbore instability not yet to be fully understood or addressed. This paper demonstrates a workflow of employing Quantitative Risk Assessment technique, considering these uncertainties in terms of rock properties, pore pressure and in-situ stresses to makes it possible to survey not just the likelihood of accomplishing a desired level of wellbore stability at a specific mud pressure, but also the influence of the uncertainty in each input parameter on the wellbore stability. This probabilistic methodology in conjunction with Monte Carlo numerical modeling techniques was applied to a case study of a well. The response surfaces analysis provides a measure of the effects of uncertainties in each input parameter on the predicted mud pressure from three widely used failure criteria, thereby provides a key measurement for data acquisition in the future wells to reduce the uncertainty. The results pointed out that the mud pressure is tremendously sensitive to UCS and SHmax which emphasize the significance of reliable determinations of these two parameters for safe drilling. On the other hand, the predicted safe mud window from Mogi-Coulomb is the widest while the Hoek-Brown is the narrowest and comparing the anticipated collapse failures from the failure criteria and breakouts observations from caliper data, indicates that Hoek-Brown overestimate the minimum mud weight to avoid breakouts while Mogi-Coulomb criterion give better forecast according to real observations.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.1
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• pp.9-14
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• 2022

In this study, a smart jack-up system was developed to prevent safety accidents by performing risk analysis when a structure is lifted for maintenance. A quantitative risk analysis program that can analyze the risk using the pairwise comparison matrix analysis method was developed. The risk was analyzed in real-time for the lifting structure by connecting the program with an automatic jack-up system. Displacements were measured by the IR sensor among the components of the automatic jack-up system, and the displacements were provided to the quantitative risk analysis program. To confirm the performance of the smart automatic jack-up system, experiments were conducted on bridge and risk analysis was performed when a superstructure was lifted. A linear variable differential transformer (LVDT) was also installed on the bridge to verify the performance of the smart automatic jack-up system. The maximum displacements were measured using the devices, and the declinations were compared. The performance of the simultaneous operation of the jack-up device was verified by the analysis of variance (ANOVA).

• Journal of the Korean Institute of Gas
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• v.18 no.6
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• pp.32-39
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• 2014

To ensure the reliability of the safety system so that handing large quantities of hazardous materials in chemical plant is considered basic information in chemical process design. However, the reliability of the production system may be reduced when the reliability of the safety system emphasized in order to ensure the safety of chemical process. It is necessary to balance the reliability of the production system and reliability of the safety. In this study, a quantitative risk assessment was performed by selecting the furnace process, which is widely used in the chemical plant in order to suggest a way to ensure the safety and productivity of chemical process, based on the quantitative data. Quantitative risk assessment methodology have been used directed graph analysis methodology. It is possible to evaluate the reliability of the safety system and the production system. In this study, the optimum system design requirement to improve the safety and the productivity of the furnace is two-out-of-three logic for TT and PT.

• Journal of the Korean Society of Safety
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• v.20 no.4 s.72
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• pp.71-77
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• 2005

There are insufficient models that find problems and solutions for accident prevention through risk assessment and suggest safe work process and work instruction from foundation works to finish work for accident decrease. This paper presents a quantitative risk assessment model by analysis of risk factors in each process such as foundation, erection, structure, equipment finish and etc based on accident examples and investigation on actual condition in building. In addition, the safety management system was developed to perform risk assessment of construction and use it for effective safety training for labor.

• Proceedings of the KSME Conference
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• 2005.11a
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• pp.144.2-144.2
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• 2005

• Journal of the Korean Society of Safety
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• v.10 no.1
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• pp.56-63
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• 1995

Two methods of the numerical method of CPQRA(Chemical Process Quantitative Risk Analysis) and the manual method of IAEA(International Atomic Energy Agency) were used to estimate the individual risk and societal risk around the chemical plant. Where, the CPQRA is introduced to verify the theoritical background of the manual of international atomic energy agency. The Gaussian plume model which has a weather stability class D with velocity of 5m/s was applied to calculate dispersion of hazard material. Also, 8-point method was employed to the effects of accidents for wind distribution. Furthermore, historical record, FTA(Fault Tree Analysis) and ETA(Event Tree Analysis) were used to estimate the probability or frequency of accidents. Eventually, the individual risk shows isorisk contour and the societal risk shows F-N curve around hazard facility, especially in chemical plants. Caulculated results, which both individual and societal risk, by using IAEA manual show simillar results to those of calculation by numerical method of CPQRA.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.959-981
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• 2017

Existing Android malware detection approaches mostly have concentrated on superficial features such as requested or used permissions, which can't reflect the essential differences between benign apps and malware. In this paper, we propose a quantitative calculation model of application risks based on the key observation that the essential differences between benign apps and malware actually lie in the way how permissions are used, or rather the way how their corresponding permission methods are used. Specifically, we employ a fine-grained analysis on Android application risks. We firstly classify application risks into five specific categories and then introduce comprehensive risk, which is computed based on the former five, to describe the overall risk of an application. Given that users' risk preference and risk-bearing ability are naturally fuzzy, we design and implement a fuzzy logic system to calculate the comprehensive risk. On the basis of the quantitative calculation model, we propose a risk classification based approach for Android malware detection. The experiments show that our approach can achieve high accuracy with a low false positive rate using the RandomForest algorithm.